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README.md

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-license: llama2
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+---
+inference: false
+license: llama2
+pipeline_tag: image-to-text
+---
+
+
+# DenseConnector-with-mgm-7B Model Card
+
+## Model details
+
+**Model type:**
+DenseConnector is an open-source chatbot trained by fine-tuning LLaMA/Vicuna on GPT-generated multimodal instruction-following data.
+It is an auto-regressive language model, based on the transformer architecture.
+
+**Model info:**
+DenseConnector-with-mgm-7B was trained in 05/2024.
+
+**Paper or resources for more information:**
+https://github.com/HJYao00/DenseConnector
+
+**Paper on Hugging Face:** 
+[arxiv.org/abs/2405.13800](https://arxiv.org/abs/2405.13800)
+
+**Training dataset:**
+This model is trained on [MGM](https://github.com/dvlab-research/MGM/tree/main) dataset.
+
+**Large Language Model:**
+Vicuna-7B
+
+**How to inference**
+This model was trained based on the MGM codebase. Please replace mgm_arch.py in MGM to test our model.
+
+
+## License
+Llama 2 is licensed under the LLAMA 2 Community License, 
+Copyright (c) Meta Platforms, Inc. All Rights Reserved.
+
+**Where to send questions or comments about the model:**
+https://github.com/HJYao00/DenseConnector/issues
+
+## Intended use
+**Primary intended uses:**
+The primary use of DenseConnector is research on large multimodal models and chatbots.
+
+**Primary intended users:**
+The primary intended users of the model are researchers and hobbyists in computer vision, natural language processing, machine learning, and artificial intelligence.